Dataset Discovery has been a hot topic in the data management community.
Earlier studies [1]}, [2]}, [3]} relied on keyword search over web tables to identify essential information.
Octopus [4]} and InfoGather [5]} focused on the problem of schema complement, an important topic in exploring web tables.
Aurum [6]}, S3D [7]} and Tableminer+ [8]}, [9]} utilized knowledge bases to identify relationship between datasets.
SemProp [10]} followed this route by leveraging ontologies and word embeddings, and Leva [11]} solved a similar problem with graph neural networks.
\(D^4\) [12]} addressed the problem of column clustering in data lake tables.
Valentine [13]} provided resources for evaluating column matching tasks.
DomainNet [14]} studied the problem of disambiguation in data lakes.
